Authors (in signing order): Ruiz, M.
Title: Domain adaptation strategies in statistical machine translation: a brief overview
Journal (title, volume, start and end page): Knowledge engineering review. Vol.30. Num.5. Pag 514-520
Impact factor (SCI/SSCI/AHCI): 1.039 (JCR-Science)
Citations received: 1 (Scholar)
Other quality indices (state database and impact factor):
Abstract: Statistical machine translation (SMT) is gaining interest given that it can easily be adapted to any pair of languages. One of the main challenges in SMT is domain adaptation because the performance in translation drops when testing conditions deviate from training conditions. Many research works are arising to face this challenge. Research is focused on trying to exploit all kinds of material, if available. This paper provides an overview of research, which copes with the domain adaptation challenge in SMT.
Citation: Ruiz, M. Domain adaptation strategies in statistical machine translation: a brief overview. "Knowledge engineering review", 1 Novembre 2015, vol. 30, núm. 5, p. 514-520.